As questions like “What’s your AI strategy?” and “Are you AI-ready?” continue to fly at business leaders day in and day out, the pressure to modernize one’s business is inescapable.

For many organizations, the starting point lies in intelligent automation, also known as “the integration of AI and automation technologies to improve business processes with flexibility and speed.”

Unlike traditional automation, these technologies learn as they go, helping them become more accurate and efficient over time. They predict the needs of your users and customers while allowing your employees to be productive elsewhere by pursuing more rewarding, high-value tasks.

The value potential is truly far-reaching. Still, since there are so many intelligent automation tools to choose from and there is no shortage of use cases to try out, it can be tough to know where to begin.

To help you get started with intelligent automation, we’ve compiled a list of 4 steps to kickstart your journey. And for extra inspiration, read to the end to catch 5 examples of ways this technology is often used.

4 Steps You Can Take Now to Kickstart Your Intelligent Automation Journey

Step 1: Identify Your Business Goals and Top-Priority Challenges

As we’ve already discussed, intelligent automation is an incredibly versatile tool with many use cases. To narrow that scope, it’s best to start by identifying the business goals you want to pursue and prioritize which challenges you want to tackle first.

Some of the most common business goals and challenges that organizations chase using intelligent automation include:

  • Improving operational efficiency and productivity
  • Reducing operational costs and risks
  • Enhancing customer experience and loyalty
  • Increasing revenue and profitability
  • Boosting innovation and competitiveness
  • Ensuring compliance and security

As you’re sifting through potential goals, be sure to prioritize the business areas that need the most improvement, align with corporate goals best, and are projected to have the most impact on your business performance. Choosing a goal that checks all three of these boxes will increase your chances of achieving a high-impact first intelligent automation project, and that success will give you momentum for future projects. Additionally, be sure to take the time to determine how you’ll measure your success and progress, as you’ll want to start measuring your progress from the start of the project. But more on that later!

Step 2: Assess Your Current Processes and Capabilities

Now that you know what you want to accomplish, you can start searching for specific areas within your organization where you can make optimal progress.

Start by assessing your current processes and capabilities and where they stand relative to your goal. For each process, look for gaps and inefficiencies. Some will have a more urgent need than others, so take note of that. It’ll help you determine which processes to prioritize.

Additional criteria to inspect include the process’:

  • Volume
  • Frequency
  • Complexity
  • Variability
  • Necessary level of human involvement and intervention
  • Data sources and formats involved
  • Systems and applications involved

By carefully assessing your current processes and capabilities, you can determine the feasibility and ROI of intelligent automation for each. This will also ultimately help you select the candidate that will deliver on your goal most effectively.

Step 3: Choose the Right Intelligent Automation Tools

Now that you have the “why” and “what” down, it’s time to determine how you’ll achieve your intelligent automation goals.

You can create a customized and scalable intelligent automation solution that meets your goal by choosing the right intelligent automation tools. Your ideal tool combination will vary from one process to another, but common intelligent automation technologies that may be helpful to you include:

  • Intelligent Capture: This technology helps you capture, extract, and validate data from various sources and formats, like paper documents, emails, invoices, forms, images, and more. It uses AI technologies, like optical character recognition (OCR), natural language processing (NLP), and machine learning (ML) to automate and enhance the data capture process.
  • Robotic Process Automation (RPA): RPA helps you automate repetitive, rule-based, and high-volume tasks that humans perform using software robots or bots. RPA can mimic human actions, like clicking, typing, copying, and pasting, to execute tasks across multiple applications and systems.
  • Intelligent Process Automation (IPA): This technology helps you automate complex and end-to-end business processes that involve multiple systems, data sources, and human interactions. IPA uses a combination of automation technologies, like business process management (BPM), workflow automation, RPA, and AI, to optimize the execution of business processes. It can help you increase operational efficiency, reduce costs and risks, and enhance customer satisfaction and loyalty.
  • Content Services: Content services can help you manage the lifecycle of your content, from creation to disposal, according to your predefined policies and regulations. Content services use AI technologies, like NLP, ML, and computer vision, to analyze and tag content automatically and accurately, making it easier to organize and search for specific information. Content services can also help you transform content, whether it’s translating text or converting file formats, making it more accessible and usable.
  • Machine learning (ML): ML helps you analyze large and complex data sets, identify patterns and trends, and generate insights and predictions. ML uses algorithms and models that can learn from data and improve over time without explicit programming. ML can help you enhance decision-making, optimize performance, and discover new opportunities and solutions.

A vital element to remember when selecting tools is ensuring that they seamlessly integrate with your existing systems, as it’ll help you get the most ROI out of your implementation.

Step 4: Implement and Monitor Your Intelligent Automation Solution

Finally, it’s your chance to plan your implementation, measure the results, and optimize your solution from there. Here, you’ll want to use the measurements you determined in step #1 to evaluate your solution’s effectiveness, measure its ROI, and find improvement opportunities. Continuous improvement should always be your goal, as it’ll mean you will get the most out of your investment as time goes on.

Some of the best practices that can help you implement and monitor your intelligent automation solution are:

  • Don’t Scale Too Quickly: Once you start seeing the value intelligent automation can offer, it can be tempting to scale your solution sooner rather than later. However, it’s best to first test and refine your first intelligent automation project and measure its results and benefits. Then, you can apply what you’ve learned to expand your solution to other processes or areas that can benefit from it, too.
  • Lead Your Stakeholders Through Change: Engage your employees, customers, vendors, and partners throughout your intelligent automation journey. Communicate your vision and goals, solicit their feedback and input, and address their concerns and expectations. Possibly most importantly of all, provide them with the necessary training and support to adopt and use your intelligent automation solution. For more information on building a strong training program and leading people through change, check out our full guide to reskilling and upskilling and 4 ways to prepare your employees for digital transformation initiatives.
  • Continuously Improve and Innovate: Monitor and review your intelligent automation solution and its performance regularly. Collect and analyze data and metrics, such as efficiency, quality, cost, customer satisfaction, and revenue. Identify and resolve any issues or gaps and implement any changes or enhancements. Leverage the insights and learnings from your intelligent automation solution to drive continuous improvement and innovation.

5 Intelligent Automation Examples to Inspire You

Now that you know the steps to getting started with intelligent automation, you might be wondering what it looks like in action. To give you some inspiration and ideas, here are some examples of common intelligent automation use cases:

  1. Data Entry and Updates: Intelligent bots can complete data entry quickly with an increasingly low error rate since these technologies learn as they go and improve their efficiency and accuracy over time.
  2. Boost Security Measures: AI can be used to identify patterns at a more comprehensive scale than any human could detect, helping organizations combat the threat of security breaches and other disasters.
  3. Recruitment: Natural language processing (NLP)-driven bots can gather and screen resumes and email candidates based on their results, letting HR teams spend less time on paperwork and more time engaging with promising candidates.
  4. Data Extraction: Intelligent bots powered by AI components like NLP and machine learning can extract unstructured data from images, PDFs, or handwritten documents, then comprehend the document’s context, allowing it to learn and make more informed, accurate decisions.

Optimize Content Management: AI can also enhance your content management solution more efficient than ever. AI algorithms can analyze and tag content automatically and with high accuracy levels, making it easier to organize and search for specific information. It can even transform content, whether it’s translating text or converting file formats.

7 Cross-Industry Intelligent Automation Use Cases
7 Cross-Industry Intelligent Automation Use Cases

Wondering how other organizations are using intelligent automation? We’ve compiled 7 examples of intelligent automation tools in action at organizations across industries.

Read Now

Launch Your Intelligent Automation Journey Today

As we’ve seen, intelligent automation is an incredibly versatile technology that can help you optimize your processes and drive innovation that sets your business apart from the rest. But to reap its full benefits, you need to have a clear and effective strategy to get started with it. By following the steps we’ve shared in this blog, you can create and implement a successful intelligent automation solution that meets your business goals and challenges.

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About Kara

As a Naviant Content Writer since 2019, Kara is passionate about helping organizations unleash the power of technology to solve their business challenges. In her weekly articles, Kara breaks down the latest research, trends, and tips in the digital transformation world, specializing in intelligent automation, the cloud, AP & HR automation, artificial intelligence, change management, and more. She is also a Copywriter for the American Marketing Association-Madison, where she contributes bimonthly articles that interview industry experts and highlight the latest marketing trends. When she’s not writing, Kara is working on her latest art project, scoping out new music, or out for a run.